RightChain.ai Plotting

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RightChain.ai Plots

1. Plot Types 2. How to Customize Plots 3. Plot Controls 3.1.

X and Y Axis Dimensions Clustering and Classification

3.2. 3.3. 3.4.

Plot Properties

Labels and Statistics 4. How to Add, Modify, or Remove Custom Plots

1. Plot Types RightChain.ai allows users to create a wide variety of visualizations and plot types highlighting and revealing key patterns from input data and/or optimization solutions. Plot types include (a) One/Two Dimensional Visualizations including Pareto Charts, Bar Charts, and Histograms; (b) Two/Three Dimensional Visualizations including XY/Scatter Plots, and Partitions; (c) Predictive Visualizations including Forecasts and Outliers; (d) Relationship Visualizations including Network Charts and Correlation Matrices; and Geographic Charts (e.g. Maps).

1.1 ONE/TWO DIMENSIONAL VISUALIZATIONS 1.1.1 Pareto Charts

1.1.2 Bar Charts 1.1.3 Histograms

1.2 TWO/THREE DIMENSIONAL VISUALIZATIONS 1.2.1 XY/Scatter Charts 1.2.2 Partitions

1.3 PREDICTIVE VISUALIZATIONS 1.3.1 Forecasts 1.3.2 Outliers 1.4 RELATIONSHIP VISUALIZATIONS 1.4.1 Network Charts 1.4.2 Correlation Matrices 1.5 GEOGRAPHIC VISUALIZATIONS 1.5.1 Maps

RightChain™ Plots

2. How to Customize Plots Plots shown on any tab of the application can be customized using the “Plot Controls” section in the Sidebar Interactions Area. The image below shows that by clicking on the “Plot Controls” label on the sidebar (circled in red) all plot customization options appear.

No matter the application module, plot controls are available at the bottom of the sidebar, with options appearing upon clicking on the words “Plot Controls”.

3. Plot Controls Available plot controls vary based on the selected plot type, and may change when switching between tabs. The most common plot controls can be broken into a few categories (in the next sections). 3.1 X-Axis, Y-Axis, Dimension The X and Y Axis controls are used to select which columns in the data set should display on each axis, and the Dimensions are the columns in the data to aggregate by (such as Product Type or Category Segment Name). Dimensions allow for grouping and displaying aggregate information in large data set for the dimension or dimensions chosen. Multiple dimensions can be selected for a single plot, and a dimension selected can be set as the X or Y axis of the plot if desired.

RightChain™ Plots

3.2 Clustering and Classification Clustering parameters can be used to create clustered groups using the “Bases” and “# of Clusters” provided. The resulting k-means clusters can be visually assessed by changing the “Color Basis” plot control to be “Cluster”. Some example uses of clustering include creating ABCD SKUs based upon their picking frequency and volume, creating “Very Heavy”, “Heavy”, “Medium”, and “Light” transportation route days based upon the number of stops, time per stop, and distance between stops; or identifying SKUs with “Very Problematic Inventory”, “Problematic Inventory”, and “Non Problematic Inventory” based upon a combination of $s, days, and cube on hand.

3.3 Plot Properties (such as Marker Color, Shape, and Size) Multiple properties of how the plots looks are customizable and include everything from the type of marker for each data point to the size and color scheme of those markers. Colors can be based on specific metrics or dimensions as well as the cluster groups. 3.4 Labels and Statistics Plot markers can also optionally display with text labels of their cluster number or other column data. Plot statistics set in the sidebar determine what stats will be shown in the statistics table or drawn on the plot if it is an XY plot. For XY plots where both axes are metrics, stat lines are drawn for just the data in view and reported below the plot just for that filtered subset, and they’re updated as you pan around the plot or zoom in on plotted data.

RightChain™ Plots

The default “Metric Statistics” are Mean and Median if nothing is selected, and the default “Dimension Statistics” are “Most Common” and “# of Unique Values”. The ability to set the “Statistics Bases” allows you to include table statistics for columns in the data set that are not currently shown in the plot.

4. How to Add, Modify, or Remove Custom Plots Underneath the “Plot Controls” label on the sidebar, three custom plotting buttons can be found that enable you to add , modify , or remove custom plots. Adding a custom plot creates a new tab with the name and description provided and uses the selected “Plot Type” to visualize the data set.

4.1 Modify or Remove Custom Plots Custom plots can also be modified using the center button to change the name, description, and/or type of the tab that is currently in view. To modify another tab, that tab should be selected first and then the modify button can be used to update it.

RightChain™ Plots

Finally, the remove button

erases the current tab and plot that is on it.

RightChain™ Plots

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